Automatic Data Processing Company Income Statement Analysis for the Financial Year 2018 and 2019
According to the company’s financial statement, revenue reported in 2018 and 2019 were $13,328 million and $14,175 million, respectively. The figures depict an increase in the company’s realized revenue between 2018 and 2019 by 6.355 percent. Moreover, the cost of goods sold increased from $7,279 million in 2018 to $7,555 million in 2019. It shows a growth increment in sales by 3.79 percent (WSJ markets, 2021). The firm’s gross income increased from $6,049 million in 2018 to $6,620 million in 2019. There was an increase in the firm’s expenses from $3,471 million in 2018 to $3,616 million in 2019. The company’s net income rose from $1,885 million in 2018 to $2,293 million in 2019. The analysis shows growth of revenue and net income for the Automatic Processing Company (WSJ markets, 2021). Hence, the income statement shows that the company’s good performance based on the increase in the total net income of 21.64 percent between 2018 and 2019.
Financial Position Analysis for Automatic Processing Company in 2018 and 2019
A company needs to determine its financial position statement due to the significant role it contributes to the company. The financial report, also referred to as a balance sheet, is essential in determining its health (Herranz & Martínez-Carrascal, 2017). The balance sheet shows the assets, liabilities, and the company’s capital outstanding as per the preparation period. Automatic Data Processing company reported an increase in the total investment from $38,849 million in 2018 to $41,888 million in 2019. The accumulation of 7.82 percent shows that the entity acquired more assets in 2019 than in 2018. There was also an increase in the company’s total liabilities from $34,113 million in 2018 to $36,488 million in 2019. It depicts an increase in the company’s obligation by 6.96 percent between 2018 and 2019 (WSJ markets, 2021). Total liabilities are deducted from the entire asset to obtain the capital for the firm. The total capital for 2018 and 2019 will be calculated as shown below.
- 2018 capital = $38,849 million – $34,113 million = $4,736 million
- 2019 capital = $41,888 million – $36,488 million =$5,400 million
The company capital increased from $4,736 million to $5,400 million from the calculations above, a 14.02 percent increase. An increase in the capital implies that the company realized growth in its investment capacity between 2018 and 2019. Thus, the balance sheet analysis above confirms that the company has been experiencing good performance to generate revenue returns from its operating activities.
Cash Flow Statement Analysis for Automatic Data Processing Company
Cash flow statements are significant in analyzing the profitability of the company. The cash flow statement typically captures the company’s cash, unlike the balance sheet and the income statement that focus on the accrual basis (Gulin & Hladika, 2017). Automatic Data Processing firm reported an increase in the net operating cash flow from $2,515 million in 2018 to $2,618 million in 2019. It implies that the cash received from the operational activities of the entity increased by 4.1 percent. Moreover, the organization’s net investing cash flow dropped from $2,505 million in 2018 to $2,198 million in 2019 (WSJ markets, 2021). A drop in the investing cash flow implies that the firm spent less cash in investing activity in 2019 than in 2018.
The last component of the cash flow statement that looks at the financing activities indicates a decline from $1,656 million to $208 million. The fall suggests that the cash outflow associated with different company financing activities was reduced in 2019. The company recorded an increase in its overall cash inflow from $2,309 million in 2018 to $2,526 million in 2019, a 9.4 percent increase (WSJ markets, 2021). The rise indicates the excellent performance of the firm in generating cash from its operations.
Financial Ratio Analysis of Automatic Data Processing Company
Financial ratios play a critical role in analyzing the performance of a firm within a specific timeline. The entity can know its profitability, the extent to which it relies on debt, ability to pay current, and efficiency of its operational activities (Andjelic & Vesic, 2017). The financial ratios are grouped into different categories: profitability ratio, liquidity ratio, leverage ratio, activity ratio, and efficiency ratio. Each of these ratios is used as an indicator in determining a given aspect of the industry’s performance.
Liquidity Ratio
The liquidity ratio is vital in determining the ability of the firm to meet short-term obligations. The shared liquidity used includes the current ratio, quick ratio, and cash ratio. The three ratios are calculated below with the following interpretations.
Current Ratio
Current ratio = current asset / current liabilities:
- 2018 current ratio = $31,823 million / $30,413 million = 1.05
- 2019 current ratio = $34,342 million / $32,185 million = 1.07
From the calculations above, the current ratios for 2018 and 2019 are 1.05 and 1.07, respectively. The proportions are more significant than one implying that the industry has more current assets than current liabilities. A current balance above a value of 1.00 indicates that the firm can settle its short-term debt without constraint. Thus, the Automatic Data Processing Company performed well both in 2018 and 2019 in meeting its current liabilities obligation.
Quick Ratio
The quick ratio indicates how well a firm can settle its current obligation without the inventory.
Quick ratio = (Current asset – Inventories) / Current liabilities:
- 2018 quick ratio = ($31,823 million – $1,984 million) / $30,413 million = 0.98
- 2019 quick ratio = ($34,342 million – $2,439 million) / $32,185 million = 0.99
From the calculations above, the reported quick ratios for 2018 and 2019 are 0.98 and 0.99, respectively. The balances reported in 2018 and 2019 are lower than 1.00, implying that the current asset minus the inventories are less than the current liabilities. Thus, the entity’s inability to depend on existing assets less stock to meet its short-term obligation. The Automatic Data Processing Company will face a constraint in settling its current liabilities using current assets without the inventory.
Cash Ratio
The cash ratio indicates the ability of the entity to pay its current liability using cash.
Cash Ratio = Cash / current liabilities:
- 2018 cash ratio = $2,170 million / $ 30,413 million = 0.07
- 2019 cash ratio = $1,949 million / $32,185 million = 0.06
The workings above show that the cash ratio decreased from 0.07 to 0.06 between the 2018 and 2019 periods. The cash ratios for 2018 and 2019 are less than one indicating that the value of cash is less than the current liabilities. Automatic Data Processing Company cannot depend on only its cash to meet its current liabilities.
Profitability Ratio
The profitability ratio indicates how much benefit a firm can derive from its operation. It looks at profits generated from the different classifications of assets, equity, and industry sales. A firm can establish how efficient it is in generating income from various activities through the profitability ratios. Some of the profitability ratios include net profit margin, return on asset, and return on equity.
Net profit margin. Net profit margin indicates how much net profit is derived from the firm’s sales. The higher the value, the more the net profit generated from the sales.
Net Profit Margin = Net Profit / Sales:
- 2018 net profit margin = $1,885 million / $13,328 million = 0.14
- 2019 net profit margin = $2,293 million /$14,174 million = 0.16
The calculations above show that the entity increased the net profit derived from sales in 2019 compared to that of 2018. Hence, the firms’ performance in terms of net profit generated from 2019 from sales.
Return on Asset (ROA): Return on asset shows how much net income an entity can generate from the investment. Net income is divided by the total investment to obtain a return on asset, as shown below.
- 2018 Return on Asset = $1,885 million / $38,849 million = 0.05
- 2019 Return on Asset = $2,293 million / $41,888 million = 0.05
The firm generates 0.05 net income from total asset for the two periods. The value is quite low since it is less than one and the firm needs to put policies in place to increase its Return on asset.
Leverage ratio
Leverage ratios are used to assess how much a firm depends on debt as its finance source. An industry that relies on more debt compared to equity is highly levered. High-levered firms have obligations to settle their debt financing, making them risky for investors. An entity with a 0.5 and above leverage ratio has high financial volatility since it’s required to pay its debt holders.
Debt equity ratio = Total debt / Equity:
- 2018 debt-equity ratio = $2,002 million / $4,736 million = 0.42
- 2019 debt-equity ratio = $2,002 million / $5400 million = 0.37
There is a significant drop in the debt-equity ratio implying that in 2019, the company increased its reliance on equity. It indicates less riskiness of the firm since the ratio is less than 0.5.
Debt to asset ratio = Total debt /total asset:
- 2018 debt to asset ratio = $2,002 million / $38,849 million = 0.05
- 2019 debt to asset ratio = $2,002 million / $41,888 million = 0.05
The company relies more on asset for financing in comparison to debt. Hence, the firm is not financially risky since it depends on its asset and not borrowing from outsiders for financing.
Activity Ratios
Activity ratios are essential in determining the effectiveness of the operation of a company. They are also known as the turnover ratios. Activity ratios indicate the frequency at which an entity can generate cash and sales from its assets. The regular the number of times, the more efficient the firm in its operations. Some of the activity ratios include account receivable turnover, payable account turnover.
Account receivable turnover = Credit Sales / Account receivable:
- 2018 = $13,328 million / $1,984 million = 6.72times
- 2019 = $14,175 million / $2,439 million = 5.81times
Automatic Data Processing Company generates payment from debtors at a frequent of 6.72 and 5.18 in 2018 and 2019, respectively.
Conversion of EBIT to EBITDA = EBITDA / EBIT:
- 2018 = $2,956million / $2,578million = 1.15
- 2019 =$3,414million / $3,005million = 1.14
The company converts EBIT to EBITDA at a frequency of 1.15 for 2018 and 1.14 for 2019, implying low conversion efficiency.
Comparison between Automatic Data Processing and Paychex Company
Financial ratios are essential in comparing the performance of different companies within a specified period. The profitability, efficiency, liquidity, and leverage of the two companies under comparison are determined. In comparing Automatic Processing Data Company and Paychex’s performance, the current ratio, net profit margin, return on asset, and account receivable turnover will be used. 2018 and 2019 will be the base period under the analysis for the two entities. The numerical value of Paychex is obtained from Finance Yahoo while that of ADP from JSD Markets.
Current Ratio
Paychex firm had a current ratio of 1.09 and 1.17 in 2018 and 2019, respectively. On the other hand, ADP has a current ratio of 1.05 and 1.07 in 2018 and 2019. The current ratio for Paychex in each period is higher than that of ADP. In settling existing obligations, Paychex Company performs better than the ADP entity.
Net Profit Margin
Paychex’s net profit margin in 2018 and 2019 is 0.28 and 0.27, respectively, while ADP is 0.14 and o.16 in 2018 and 2019, respectively. It clearly shows that Paychex generated higher income than ADP in the two periods. Thus, Paychex’s performance in generating profit from sales higher than that of ADP.
Return on Asset (ROA)
Return on asset shows the income an entity derives from the investment it owns. The table above indicates that the return on Paychex’s assets is 0.13 and 0.27 in 2018 and 2019, respectively. On the other hand, the ADPs assets were 0.05 for both 2018 and 2019. According to the table above, the Return on Asset for Paychex Company is higher than that of ADP. Thus, the excellent performance of Paychex company in generating profit from the asset as compared to ADP.
Account receivable turnover
Account receivable turnover indicates the frequency at which a firm receives payment from the debtor. According to the table above, the Paychex Company account receivable turnover was 1.09 and 1.17 for 2018 and 2019, respectively. In contrast, those for ADP are 1.05 and 1.07. The Paychex debtors make regular payments as compared to those of ADP. Paychex company’s higher turnover gives it efficient performance in collecting income from credit sales than ADP company.
Conclusion
According to the income statement, balance sheet, and cash flow accounts, Automatic Data Processing company depicts an increasing trend in its operation. For instance, increase in the sales, net income, cash inflows, assets, capital for the basis period 2018 and 2019. The increase is favorable to the company since it indicates the growth of the entity in its operations. Under the financial ratios, ADP company faces no constraint in paying its current obligation by using current liabilities. However, the quick ratio and cash ratio show limitations of the company in settling its current liabilities. ADP is less volatile due to less dependence on the debt than the debt-equity ratio below 0.5. Although Paychex is in thousands of dollars, Paychex performs better, although ADP firm operations are in millions of dollars. The ratio analysis established how Paychex outperforms ADP using various ratios. Thus, the ADP management needs to explain the debtor’s payment policies, company investment activities, capital structure policies. The answers will be essential in understanding why the company operates in millions of dollars yet performs lower than Paychex working in thousands of dollars.
References
Andjelic, S., & Vesic, T. (2017). The importance of financial analysis for business decision making. In M. C. Karavidic, S. Karavidic, & S. Ilieva (Eds.), Employment, Education and Entrepreneurship (pp. 9-25). American Psychological Association. Web.
Finance Yahoo. (2021). Paychex Inc.
Gulin, D., & Hladika, M. (2017). Information capacity of cash flow statement – Do we use it enough? Proceedings from MultiScience–XXXI. microCAD International Multidisciplinary Scientific Conference, Miskolc, Hungary, 20-21.
González, F. H., & Martínez-Carrascal, C. (2017). The impact of firms’ financial position on fixed investment and employment. An analysis for Spain. SSRN Electronic Journal, (1714), 1-30.
WSJ Markets. (2021). Automatic Data Processing Inc. Web.